Local and regional banks, as financial institutions close to their communities, play a significant role in meeting the economic and social needs of society. In recent years, innovative technologies such as blockchain and artificial intelligence (AI) have provided new opportunities to enhance efficiency, transparency, and security in banking processes. One of the practical applications of these technologies is social credit scoring, which, by integrating social data and intelligent tools, can lead to improved service delivery by local and regional banks.

1. Concept of Social Credit Scoring and Its Importance

Social credit scoring is an approach that utilizes information related to behavior, social relationships, local economic activities, and qualitative evidence to assign a socio-economic rating to individuals and small businesses. This method goes beyond traditional credit scoring metrics (such as banking history and income) to include social and local indicators. As a result, local and regional banks can use this model to make more informed decisions regarding loan disbursement, credit facilities, and financial services.

2. The Role of Blockchain in Social Credit Scoring

Blockchain, as a decentralized and distributed technology, provides a secure and transparent foundation for storing and transferring credit-related data. The benefits of using blockchain in social credit scoring include:

  • Transparency and Immutability: All transactions and credit data are recorded in a distributed ledger, making any changes visible to all stakeholders.
  • Increased Trust: Storing data on blockchain enhances trust among local banks, customers, and other stakeholders, reducing the risk of fraud or misuse.
  • Easy Access to Local Information: By integrating local data (such as information about small businesses, local associations, and NGOs) into blockchain, banks can achieve a more comprehensive understanding of the socio-economic creditworthiness of individuals or businesses.

3. Artificial Intelligence and Social Data Analysis

AI, with its capability to identify patterns and process large volumes of structured and unstructured data, provides valuable tools for analyzing social and local data for banks:

  • Detection of Hidden Patterns: AI can uncover hidden patterns in the financial and social behaviors of individuals, establishing meaningful relationships for credit scoring.
  • More Accurate Risk Prediction: By combining local, cultural, and economic data, AI can predict credit defaults more accurately, assisting banks in making better decisions.
  • Personalized Services: AI-driven algorithms analyze user data to deliver financial services tailored to individual and local needs.

4. Synergy Between Blockchain and AI for Social Credit Scoring

The combination of blockchain and AI can create a secure, transparent, and dynamic system for social credit scoring. In this approach:

  • Blockchain ensures the data is credible, immutable, and traceable.
  • AI uses these reliable data sources to enhance credit scoring models and generate deeper insights.

This synergy results in better access to local financial services, reduced credit risk, and improved economic well-being for communities.

5. Challenges and Considerations

Despite the significant advantages, implementing this approach faces several challenges:

  • Privacy: Protecting personal and local data is a critical concern requiring appropriate legal and ethical frameworks.
  • Data Standardization: Optimizing the use of AI requires high-quality, well-structured social data.
  • Costs and Infrastructure: Establishing and maintaining blockchain and AI infrastructure demands substantial investment and expertise.

6. Role of the Innovation and Social Economy Research Institute at the University of Tehran

The Innovation and Social Economy Research Institute at the University of Tehran, through interdisciplinary research and analysis of international experiences, can contribute to developing strategies for applying blockchain and AI in social credit scoring. By organizing conferences, workshops, and publishing research findings, the institute supports policymakers, local banks, and other stakeholders in advancing sustainable development and strengthening the local economy.

Conclusion

Blockchain and AI, by providing a secure, transparent, and intelligent platform for social credit scoring, offer new possibilities for local and regional banks. By utilizing these technologies, banks can make better decisions and provide more suitable services to local customers. In this context, the Innovation and Social Economy Research Institute at the University of Tehran plays a vital role in identifying opportunities, challenges, and practical solutions for effectively applying these technologies.